Energy-Efficient Bio-Inspired Computing Architectures

The growing energy demand of IT and AI systems is pushing current computing architectures to their fundamental limits. The collaborative project neuroNODE addresses this challenge by developing novel microelectronic components that combine extremely high processing speeds with very low energy consumption.

The objective is to establish a bio-inspired, neuromorphic architecture that integrates different physical technologies within a hybrid framework. At its core are low-loss superconducting logic switching elements that exploit quantum effects and enable exceptionally high clock rates. These are coupled with integrated optical components that provide efficient, broadband interconnection of circuit modules.

Through the targeted integration of superconducting and photonic technologies, optoelectronic-superconducting network and computing structures with high scalability are created. In the long term, these architectures are intended to form the basis for complex, energy-efficient computing systems of the next generation.

Funded by the Free State of Thuringia from resources of the European Social Fund Plus (Grant No. 2025 FGR 0082).